Disease associated antibody phenotypes and probabilistic seroprevalence estimates during the emergence of SARS CoV 2

Serological studies are critical for understanding pathogen−specific immune responses and informing public health measures (1,2). By developing highly sensitive and specific trimeric spike (S)−based antibody tests, we report IgM, IgG and IgA responses to SARS−CoV−2 in COVID−19 patients (n=105) representing different categories of disease severity. All patients surveyed were IgG positive against S. Elevated anti−SARS−CoV−2 antibody levels were associated with hospitalization, with IgA titers, increased circulating IL−6 and strong neutralizing responses indicative of intensive care status. Antibody−positive blood donors and pregnant women sampled during the pandemic in Stockholm, Sweden (weeks 14−25), displayed on average lower titers and weaker neutralizing responses compared to patients; however, inter−individual anti−viral IgG titers differed up to 1,000−fold. To provide more accurate estimates of seroprevalence, given the frequency of weak responders and the limitations associated with the dichotomization of a continuous variable (3,4), we used a Bayesian approach to assign likelihood of past infection without setting an assay cut−off. Analysis of blood donors (n=1,000) and pregnant women (n=900) sampled weekly demonstrated SARS-CoV-2-specific IgG in 7.2% (95% Bayesian CI [5.1−9.5]) of individuals two months after the peak of spring 2020 COVID−19 deaths. Seroprevalence in these otherwise healthy cohorts increased steeply before beginning to level−off, following the same trajectory as the Stockholm region deaths over this time period.